Clinical Research Postdoctoral Fellow
|Date Posted||April 30, 2017|
|Hours Per Week||40|
|PAVIR Job ID||LEE1701.17|
Dr. Jennifer Lee, M.D., Ph.D. at Stanford University is seeking a Clinical Research Postdoctoral Fellow to analyze NIH-supported projects assessing androgen-estrogen balance and cardiometabolic biomarkers using molecular and genetic epidemiologic longitudinal research-based data from multiple large cohorts of unrelated individuals and of families.
The Clinical Research Postdoctoral Fellow will be funded through Palo Alto Veterans Institute for Research (PAVIR) and will hold a Postdoctoral Fellow appointment through Stanford University and will have access to Stanford resources, benefits, email, etc. The Clinical Research Postdoctoral Fellow will work at Stanford University Medical Center, and will be considered a PAVIR employee (paid by PAVIR).
This is a regular, full time (40 hours/week), Exempt position.
Dr. Lee is an Associate Professor of Medicine (Endocrinology, Geriatrics, and Metabolism) at Stanford University Medical Center and Staff Physician at Palo Alto VA. She is an endocrinologist and epidemiologist (PhD, Stanford), and also Chief Medical Officer at the Palo Alto VA Cooperative Studies Program Coordinating Center (CSPCC), which coordinates many multi-site large clinical trials. The CSP is responsible for innovative large clinical trials and observational epidemiology studies in the VA. She is also site co-director of BD-STEP (Big Data Scientist Training Enhancement Program), a collaborative between National Cancer Institute and Veterans Health Administration, which trains postdocs/graduate students to be big data scientists in the use of EHR-data to impact cancer care. She is co-Investigator in VA’s national Million Veteran Program and is NIH-supported.
The Postdoc will also have the opportunity to work with very large electronic health records (EHR) such as the VA’s (longest running EHR of about 8 million people per year), administrative databases, and NIH-supported longitudinal research cohorts such as (but not limited to) Women’s Health Initiative, Cardiovascular Health Study, MrOS, and SWAN. Methods will include evaluating trajectories of hormonal and metabolic biomarker alterations (and gender and racial/ethnic differences) on progression of and responses to treatments for cardiovascular diseases, metabolic syndrome, glycemic dysregulation and diabetes, cancers, fractures, and cognitive function.
The Postdoc will coordinate collaborating and networking with Stanford, VA, and nationwide colleagues, prepare manuscripts for publication for ongoing NIH-supported and VA-supported studies, and contribute to novel projects/proposals. These may include VA’s national Million Veteran Program (recruiting a million veterans for genetic and clinical epidemiological studies) and projects to advance the learning healthcare system and more pragmatic and novel clinical trials.
The Postdoc will be mentored to serve as Co-Investigator on proposals, and to obtain funding towards becoming an independent investigator.
PAVIR is a nonprofit foundation affiliated with the Veterans Affairs Palo Alto Health Care System (VAPAHCS). As a condition of employment, all PAVIR employees are required to have an approved appointment with VAPAHCS and complete a background check before they can commence work.
- Work with and analyze data from relatively large longitudinal datasets with repeated measures of biomarkers (also genetic, epigenetic, etc) covariates over many years of follow-up; conduct data quality assessments (methodology and validation).
- Prepare manuscripts for publication and study grant proposals for submission, present work at conferences and talks.
- Coordinate with collaborating hormone/biomarker labs that perform measurements of hormones from frozen bio-specimens.
- Work in collaboration with study investigators locally and nationally.
EDUCATION: Ph.D. in Biostatistics, Statistics, Epidemiology, Medical/Bio Informatics, Genetic or molecular epidemiology, Health Services/Outcomes Research, or in a related quantitative field
- Two years or more experience working in population health sciences research.
- One year or more working with large longitudinal datasets/databases.
- Understanding of medicine or health field is highly desired.
Knowledge / Skills / Abilities:
- Proficiency in SAS (preferred statistical software) and SQL with data management skills is highly desired. R and UNIX operating systems preferable too. Genetic epidemiology software and/or Python or other would be advantageous, Markov modeling, etc.
- Experienced in a variety of research techniques/methods for longitudinal with repeated measures of exposures (propensity score matching, IPBW, machine learning, survival analyses), health services research, and genetic epidemiological research and follow-up data collection.
- Familiarity with VA EHR-based data (Corporate Data Warehouse) or other EHR-based databases, claims data would be desirable;
- Attention to detail and good organizational skills are essential;
- Good computer, writing, and speaking communication skills;
- Ability to apply knowledge of development of new methods or procedures to the coordination of the study/program;
- Ability to use library resources for information on scientific/applied aspects of study.
- Demonstrated ability to work independently as well as a contributor in a collaborative team environment
Environmental Conditions / Physical Demands:
Physical: Sitting in front of a computer for potentially long periods of time, repetitive movement, etc.
Environmental: Exposure to an office environment.
PAVIR engages in nonprofit medical research and works with sponsors and the Veterans Affairs Palo Alto Health Care System (VAPAHCS) in administering funds for conducting research to find new and improved ways to combat human disease and help people with disabilities. Please refer to our website for additional information: www.pavir.org.
PAVIR is pleased to be an Equal Opportunity Employer for Minorities, Females, Protected Veterans, and Qualified Individuals with a Disability.
- Medical Insurance
- Vision Insurance
- Dental Insurance
- Life Insurance
- Long-term Disability
- Short-term Disability
- Flexible Spending Account
- Employee Assistance Program
- Commuter Benefit